Influencing Factors of Spatial Heterogeneity of Land Surface Temperature in Nanjing, China

Abstract

The environment and climate significantly affect the land surface temperature (LST) of a city. Previous studies have revealed that LST exhibits significant spatial heterogeneity primarily caused by a combination of natural factors and human activities. Based on this, the introduction of point of interest data of the 'production-living-ecological space' divides the influencing pattern into a comprehensive description of human activities supplemented by natural factors, resulting in the precise influencing factors of spatial heterogeneity of LST. Taking Nanjing (Jiangsu Province, China) as a case study, this study uses Landsat-8 remote sensing images, point of interest data, and other data to establish a geographically weighted regression model that combines natural factors and human activities. The main research results are as follows: First, the LST of Nanjing ranged from 19.9 °C to 47.6 °C, whereas the distribution trend was 'low at both ends and high in the middle.' Second, there is no multicollinearity of the influencing factors, the fitting degree of LST and each influencing factor reached 0.87. The regression coefficients were high and exhibited both positive and negative values, implying that spatial heterogeneity exists among the influencing factors and LST. Finally, the ranking of how all factors influence the LST followed the order of water area > forest and grassland > ecological space > slope > production space > elevation > living space. The research results have practical significance for improving the quality of life of urban residents and providing a critical theoretical basis for optimizing urban human settlements.